We present an instance segmentation algorithm trained and applied to a CCTV recording of beef cattle during a winter finishing period. A fully convolutional network was transformed into an instance segmentation network that learns to label each instance of an animal separately. We introduce a conceptually simple framework that the network uses to output a single prediction for every animal. These results are a contribution towards behaviour analysis in winter finishing beef cattle for early detection of animal welfare-related problems.
@article{arxiv.1807.01972,
title = {Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network},
author = {Aram Ter-Sarkisov and Robert Ross and John Kelleher and Bernadette Earley and Michael Keane},
journal= {arXiv preprint arXiv:1807.01972},
year = {2018}
}